COVID-19 is a global pandemic that has resulted in widespread negative outcomes. Face masks and social distancing have been used to minimize its spread. Understanding who will engage in protective behaviors is crucial for continued response to the pandemic. We aimed to evaluate factors that are indicative of mask use and social distancing among current and former college students prior to vaccine access. Participants (N = 490; 67% female; 60% White) were current and former U.S. undergraduate college students. Perceived effectiveness and descriptive norms regarding COVID-19 safety measures, COVID-19-related news watching and seeking, state response timing to stay-at-home mandates, impulsivity-like traits, affect (mood), and demographic variables were assessed. Results found that greater perceived effectiveness indicated increased personal compliance within and across behaviors. Greater norms related to compliance within behaviors (e.g., indoor norms related to indoor compliance). Increased perceived stress, anxiety, and negative affect indicated greater compliance. More positive affect was associated with less compliance. Being non-White, compared to White (p < 0.001), and female, compared to male (p < 0.001), were associated with greater compliance. Overall, early implementation of stay-at-home orders, exposure to COVID-19-related news, and increased perceived effectiveness are crucial for health safety behavior compliance. Findings are important for informing response to health crises, including COVID-19.

Common factors are increasingly used to model the structure of psychopathology ("p"), personality (General Factor of Personality [GFP]), pathological personality (General Factor of Pathological Personality [GFPP]), and intelligence ("g"). Using 4 waves spanning ages 18 -29 in a cohort of college students (baseline n ϭ 489), this study used indicators of psychopathology, personality, pathological personality, and cognitive functioning to compare models that included Cognitive Functioning, p, GFP, GFPP, and a "Big Everything" factor (which included cross-domain measures as indicators). GFP, GFPP, and p exhibited substantial overlap, and the Big Everything factor accounted for considerable variance in psychopathology, personality, and pathological personality indicators. Only a self-report measure of cognitive functioning loaded significantly onto the Big Everything. This study highlights concerns in the pursuit of identifying and reifying common factors based on the modeling of residual variances and limitations of using factor modeling to determine the structure of psychologically relevant phenomena.

Adverse childhood experiences (ACEs) are related to a host of deleterious physical and mental health outcomes. The ACE–International Questionnaire (ACE-IQ) was developed to assess categories of ACEs (e.g., sexual, emotional, and physical abuse) in internationally representative samples. Though the ACE-IQ has been used world-wide, little work has examined the structure of this measure. Further, much of the modeling techniques implemented lacked theoretical rationale. The present work used two principal components analyses (PCA) to evaluate the ACE-IQ structure using both the identified ACE categories as defined by the World Health Organization (WHO) and using the ACE-IQ items as individual indicators. Using the WHO method, a two-component structure was indicated. Alternatively, a PCA of the individual items yielded a six-component structure. Results highlight the importance of theoretically grounded measure evaluation and the potential distinctions amongst types of ACEs. Implications and future directions for research and practice are discussed.

No abstract

Limited research has examined a comprehensive set of predictors when evaluating discharge placement decisions for infants exposed to substances prenatally. Using a previously validated medical record data extraction tool, the current study examined prenatal substance exposure, infant intervention (i.e., pharmacologic, or non-pharmacologic), and demographic factors (e.g., race and ethnicity and rurality) as predictors of associations with discharge placement in a sample from a resource-poor state ( N = 136; 69.9% Non-Hispanic White). Latent class analysis (LCA) was used to examine whether different classes emerged and how classes were differentially related to discharge placement decisions. Logistic regressions were used to determine whether each predictor was uniquely associated with placement decisions. Results of the LCA yielded a two-class solution comprised of (1) a Low Withdrawal Risk class, characterized by prenatal exposure to substances with low risk for neonatal abstinence syndrome (NAS) and non-pharmacologic intervention, and (2) a High Withdrawal Risk class, characterized by a high risk of NAS and pharmacologic intervention. Classes were not related to discharge placement decisions. Logistic regressions demonstrated that meth/amphetamine use during pregnancy was associated with greater odds of out of home placement above other substance types. Future research should replicate and continue examining the clinical utility of these classes.